Sexual dimorphism (differences between males and females) in psychopathology is common, is observed across species, and occurs early in development. The etiologic pathways that lead to sex differences in psychopathology stem from complex interactions among genetic, cognitive, and neural factors that vary as a function of developmental stage. However, past studies have been insufficiently powered in the size of their samples and the number of measures assessed to model these risk factors systematically within or between males and females, within and across multiple psychopathologies, or across developmental stages. Because of these limitations, we have an incomplete understanding of the neurobiology of sex differences in psychopathology in children, which has hindered timely diagnosis and treatment. There is a pressing clinical need to better identify early risk factors fr developing psychopathology, as current pharmacological and psychotherapeutic strategies to overcome the burgeoning threat of lifelong psychopathology are of limited efficacy, have adverse side-effects, and in most cases are not curative. Compelling recent data in youth have implicated key neurobiological disruptions critical for cognitive processing throughout development, most notably in prefrontal, limbic, and striatal neural circuits that may be transdiagnostic and conditioned on sex. Advances in the genetic basis of cognitive regulatory function have been translated into increased characterization of the neurocircuitry that subserves psychopathology. This proposal aims to leverage the large multimodal dataset of the Philadelphia Neurodevelopmental Cohort (PNC) to address the pressing questions of which core risk factors predict specific forms of psychopathology conditioned on sex (i.e. within males and within females), which factors explain sexual dimorphism in childhood-onset psychopathologies, and when sex differences in psychopathology emerge. To accomplish these aims, we will use state-of-the-art high-dimensional modeling methods to develop a parsimonious risk model that integrates clinical, cognitive, genetic, and neural factors in the PNC database to predict sexual dimorphism in childhood-onset psychopathology. We will model clinical (key symptom dimensions), cognitive, and genetic (genome-wide single nucleotide polymorphisms) data from a large cohort of close to 10,000 youth with a balanced (1:1) sex distribution who are between the ages of 8-21 years, and neuroimaging data in a subset of ~1,500 youth. The PNC database includes measures of normal and abnormal functioning across a wide age range to enable comparisons of psychopathology outcomes across age and in developmental subgroups. Understanding how genetic, neural, and cognitive factors interact in the development of sexual dimorphism in psychopathology has the potential to provide more precise neuroscience-informed treatment targets.